Journal Article

DeepThy‐Net: A Multimodal Deep Learning Method for Predicting Cervical Lymph Node Metastasis in Papillary Thyroid Cancer

Wei, Peiying, Yao, Jincao, Feng, Na, Wang, Liping, Xu, Huixiong, Feng, Bojian, Li, Wei, Ou, Di, Xu, Dong, Wang, Lijing, Xu, Jing, Yang, Chen, Liu, Junping, Lei, Zhikai, Yue, Wenwen, Lu, Yidan, Chen, Wencong

2022

Overview

Papillary thyroid cancer (PTC) accounts for more than 80% of thyroid cancers, and ultrasound (US) imaging is the preferred method for the diagnosis of PTC. However, accurate prediction of different patterns of cervical lymph node metastasis (CLNM) in PTC continues to be a challenge. Herein, US images and clinical factors of PTC patients from three hospitals for more than 11 years are collected, and a multimodal deep learning model called DeepThy‐Net is then developed to predict different CLNM patterns. The proposed model not only uses the convolutional features extracted by deep learning but also integrates traditional clinical factors that are highly related to lymph node metastasis. Finally, the model is tested in two independent test sets, and the experimental results show that the area under curve (AUC) is between 0.870 and 0.905, indicating clinical applicability. The proposed method provides an important reference for the treatment and management of PTC. Moreover, for PTC cases involving an active surveillance strategy, the proposed method can serve as an important CLNM early warning tool. A DeepThy‐Net model is built to extract the features of the ultrasound images and predict different cervical lymph node metastasis patterns in papillary thyroid cancer. The clinical factors recorded by doctors are also digitized and input into a fully connected network with the above‐mentioned features, and finally, the prediction results are obtained.

• Publisher: John Wiley & Sons, Inc,Wiley
• Subject: Accuracy / Cancer / computational methods / Deep learning / Feature extraction / lymph-node metastasis / Lymphatic system / Metastasis / Methods / Model testing / papillary thyroid cancer / Thyroid cancer / Ultrasonic imaging / ultrasound imaging